Knowledge graph-guided multiple sclerosis identification and therapeutic trend analysis: Real-world evidence from two large healthcare systems
The multiple sclerosis (MS) therapeutic landscape has evolved over time. We conducted a knowledge graph-guided analysis of MS-specific disease-modifying therapy (DMT) prescription trends using longitudinal real-world clinical data. We analyzed registry-linked electronic health record (EHR) data from two large independent healthcare systems between 2004 and 2022, including both academic and community practices. We developed an unsupervised phenotyping algorithm that leverages a publicly available knowledge graph and informative EHR features to identify patients with MS. After identifying MS cases, we combined the two cohorts and constructed annual time-varying knowledge graphs that capture co-occurrence patterns between DMTs and MS diagnosis. For each year, we analyzed co-occurrence patterns between DMTs and MS diagnosis using Shifted Positive Pointwise Mutual Information transformation and singular value decomposition to generate embeddings. We computed patient-wise cosine similarities and confidence intervals to quantify MS-specific DMT usage patterns. The phenotyping algorithm achieved robust performance in predicting MS diagnosis (AUROC: MGB = 0.994, UPMC = 0.922), identifying 29,169 MS patients in the combined dataset. Among commonly used standard-effectiveness DMTs, MS-specific prescriptions declined after 2011 for interferon-beta (DMT-MS cosine similarity slope = -0.019 ± 0.011, p = 0.002) and glatiramer acetate (slope = -0.013 ± 0.012, p = 0.026), from 2013-2020 for fumarates (slope = -0.028 ± 0.015, p = 0.004), and after 2014 for S1P receptor modulators (slope = -0.026 ± 0.016, p = 0.005). Among commonly used higher-effectiveness DMTs, B-cell depletion therapies (slope = 0.051 ± 0.027, p = 0.001), particularly ocrelizumab (slope = 0.020 ± 0.016, p =0.032), showed a marked increase since 2018. Natalizumab usage peaked in 2011 (slopepre-2011 = 0.063 ± 0.013, ppre-2011 < 0.001; slopepost-2011= -0.027 ± 0.008, ppost-2011 < 0.001). Other DMT classes such as cell proliferation inhibitors and chemotherapy agents, showed low usage during follow-up. These findings provide real-world evidence from two large EHR-based MS cohorts, highlighting distinct temporal shifts in the complex MS therapeutic landscape toward higher-effectiveness DMTs, particularly B-cell depletion therapy.
Authors
- Chenyi Chen (ORCID: https://orcid.org/0000-0001-8050-6754)
- Shyam Visweswaran (ORCID: https://orcid.org/0000-0002-2079-8684)
- Tanuja Chitnis (ORCID: https://orcid.org/0000-0002-9897-4422)
- Zongqi Xia (ORCID: https://orcid.org/0000-0003-1500-2589)
- Tianxi Cai (ORCID: https://orcid.org/0000-0002-5379-2502)
- Tianrun Cai
- Sara Morini Sweet
- Emily Song
- Yunqing Han
- Mohammed Moro
- Ziming Gan
- Wen Zhu
- Junwei Lu
- Tanuja Chitnis
- Weijing Tang
- Michele Morris
- Tianxi Cai
Institutions
- Harvard University (US)
- University of Pittsburgh (US)
- University of Chicago (US)
- Mass General Brigham (US)
- Carnegie Mellon University (US)
Publication Details
- Journal
- PLOS Digital Health
- Published
- 2026-08-28
- DOI
- https://doi.org/10.1371/journal.pdig.0001554
- Primary Topic
- Multiple Sclerosis Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- National Institute of Neurological Disorders and Stroke